Machine_Learning_Fundamentals

This repo contains a series of guided jupyter notebooks focusing on essential ML concepts.

Notebooks Included

Linear Regression
Data Preprocessing
Data Types and Attributes
Binary Classification
Clustering
K-Nearest Neighbors (KNN)
Naive Bayes
Comprehensive EDA performed on "Data Science Jobs and Salary" dataset

Features

Comprehensive
Practical Examples
Easy to Understand

Environment

Python
Jupyter Notebook

Usage

Learning: Use the notebooks to deepen your understanding of various ML concepts.
Teaching: Share these notebooks with students to facilitate learning in classrooms or workshops.